A Fault-Tolerant Regularizer for RBF Networks
暂无分享,去创建一个
[1] Yunqian Ma,et al. Multiple model regression estimation , 2005, IEEE Transactions on Neural Networks.
[2] Jim Austin,et al. Fault Tolerant Multi-Layer Perceptron Networks , 1992 .
[3] Alexander J. Smola,et al. Support Vector Method for Function Approximation, Regression Estimation and Signal Processing , 1996, NIPS.
[4] Chee Peng Lim,et al. A hybrid neural network model for noisy data regression , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[5] Salvatore Cavalieri,et al. A novel learning algorithm which improves the partial fault tolerance of multilayer neural networks , 1999, Neural Networks.
[6] Christopher M. Bishop,et al. Current address: Microsoft Research, , 2022 .
[7] Zhi-Hua Zhou,et al. Evolving Fault-Tolerant Neural Networks , 2003, Neural Computing & Applications.
[8] Chee Kheong Siew,et al. Universal Approximation using Incremental Constructive Feedforward Networks with Random Hidden Nodes , 2006, IEEE Transactions on Neural Networks.
[9] Naotake Kamiura,et al. An improvement in weight-fault tolerance of feedforward neural networks , 2001, Proceedings 10th Asian Test Symposium.
[10] Dhananjay S. Phatak,et al. Synthesis of fault tolerant neural networks , 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).
[11] Xia Hong. A fast identification algorithm for box-cox transformation based radial basis function neural network , 2006, IEEE Trans. Neural Networks.
[12] Sameer Singh. Noise impact on time-series forecasting using an intelligent pattern matching technique , 1999, Pattern Recognit..
[13] Alan F. Murray,et al. Enhanced MLP performance and fault tolerance resulting from synaptic weight noise during training , 1994, IEEE Trans. Neural Networks.
[14] Kwok-Wo Wong,et al. Generalized RLS approach to the training of neural networks , 2006, IEEE Trans. Neural Networks.
[15] Sheng Chen,et al. Sparse modeling using orthogonal forward regression with PRESS statistic and regularization , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[16] Sheng Chen,et al. Local regularization assisted orthogonal least squares regression , 2006, Neurocomputing.
[17] Bor-Shing Lin,et al. Higher-Order-Statistics-Based Radial Basis Function Networks for Signal Enhancement , 2007, IEEE Transactions on Neural Networks.
[18] Dhananjay S. Phatak. Relationship between fault tolerance, generalization and the Vapnik-Chervonenkis (VC) dimension of feedforward ANNs , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).
[19] Zhi-Hua Zhou,et al. Improving tolerance of neural networks against multi-node open fault , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).
[20] Chilukuri K. Mohan,et al. Modifying training algorithms for improved fault tolerance , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).
[21] Michael E. Tipping. The Relevance Vector Machine , 1999, NIPS.
[22] G. Bolt,et al. Fault models for artificial neural networks , 1991, [Proceedings] 1991 IEEE International Joint Conference on Neural Networks.
[23] Andrew Chi-Sing Leung,et al. On the regularization of forgetting recursive least square , 1999, IEEE Trans. Neural Networks.
[24] Klaus-Robert Müller,et al. Asymptotic statistical theory of overtraining and cross-validation , 1997, IEEE Trans. Neural Networks.
[25] Andrew Chi-Sing Leung,et al. Two regularizers for recursive least squared algorithms in feedforward multilayered neural networks , 2001, IEEE Trans. Neural Networks.
[26] David J. C. MacKay,et al. A Practical Bayesian Framework for Backpropagation Networks , 1992, Neural Computation.
[27] John Moody,et al. Note on generalization, regularization and architecture selection in nonlinear learning systems , 1991, Neural Networks for Signal Processing Proceedings of the 1991 IEEE Workshop.
[28] Dhananjay S. Phatak,et al. Complete and partial fault tolerance of feedforward neural nets , 1995, IEEE Trans. Neural Networks.
[29] D. Mackay,et al. A Practical Bayesian Framework for Backprop Networks , 1991 .
[30] Mark J. L. Orr,et al. Regularization in the Selection of Radial Basis Function Centers , 1995, Neural Computation.
[31] Robert I. Damper,et al. Determining and improving the fault tolerance of multilayer perceptrons in a pattern-recognition application , 1993, IEEE Trans. Neural Networks.
[32] Dan Simon,et al. Fault-tolerant training for optimal interpolative nets , 1995, IEEE Trans. Neural Networks.
[33] Lizhong Wu,et al. A Smoothing Regularizer for Feedforward and Recurrent Neural Networks , 1996, Neural Computation.
[34] Aristidis Likas,et al. An incremental training method for the probabilistic RBF network , 2006, IEEE Trans. Neural Networks.
[35] Chalapathy Neti,et al. Maximally fault tolerant neural networks , 1992, IEEE Trans. Neural Networks.